Aditi Prabhakar@aditi_prabhakar333

This project "NetPulse AI" focuses on network health monitoring and fault prediction using a Raspberry Pi and AI-powered analysis. The Raspberry Pi collects real-time system performance data—including CPU usage, temperature, signal strength, and packet loss—via sensors and serial communication. A VBScript automates data logging, storing readings in an Excel file without user intervention. The script detects anomalies and logs detailed error messages to help diagnose potential failures. This setup enables continuous monitoring without manual oversight, ensuring that network performance metrics are recorded efficiently. Once the data is logged, users can upload the Excel file to an AI-powered chatbot hosted on Hugging Face. The chatbot, built using Gradio, Pandas, and Zephyr-7B-Beta, processes the data to provide insights under three key sections: Future Performance Prediction, Risk Analysis and Potential Issues, and Preventive Actions and Recommendations. The AI detects patterns, predicts potential failures, and offers optimization strategies for network stability. Users can also download a detailed report and interact with the chatbot for additional troubleshooting and performance improvement suggestions.

🔍Create AI-driven, open-source solutions to optimize public sector network management in critical areas like predictive maintenance, total cost optimization (TOC), and energy efficiency—enhancing public sector networks' scalability, efficiency, and sustainability in underserved regions. 📅 Join us February 28–March 2, 2025: Participate online or in person in vibrant Barcelona, on the sidelines of MWC 2025, to collaborate with peers worldwide and shape the future of public sector connectivity. 👨‍🏫 Work alongside experienced industry mentors who will provide guidance and insights to elevate your solutions. 💰 $5,000 prize pool for the winners! 🏆 Compete for a chance to join the lablab NEXT incubator program! 🧑🏻‍💻 Don’t wait! Sign up now to secure your spot before the Kick-Off!